Remote Video Assessment of Ataxia via SARA home : Correlation of Pose‐Derived Endpoints with Clinician Severity Ratings

Abstract Background Remote assessment of ataxia is increasingly important for patient‐centered care and clinical research. SARA home , a validated video‐based adaptation of the Scale for the Assessment and Rating of Ataxia (SARA), enables self‐administration of key motor tasks at home. Objective The aim was to evaluate the correlation of pose‐derived gait and stance endpoints from SARA home videos with clinician‐rated severity. Methods In a multisite observational study, participants recorded SARA home tasks on consumer mobile devices via the Atom5 TM app. Clinicians rated videos using standardized criteria, blinded to automated outputs. Kinematic measures were extracted via pose estimation and aggregated to video‐level features. Videos were aggregated per participant before correlation using Spearman's ρ and Kendall's τ , with 95% cluster‐bootstrap confidence intervals. Results We analyzed 5418 gait and stance videos from 58 participants across 4 sites (gait n = 2205, stance n = 3213). Score distribution was skewed toward lower severity. For gait, clearance variability ( ρ = 0.52 [0.37–0.64]) and median‐normalized base of support ( ρ = 0.51 [0.35–0.66]) correlated most strongly with item ratings, followed by shoulder sway root mean square ( ρ = 0.43 [0.24–0.60]). Adjusted foot clearance (worse limb) correlated negatively ( ρ = −0.35 [−0.52 to −0.15]). For stance, anteroposterior sway ( ρ = 0.51 [0.36–0.65]), leg alignment variability ( ρ = 0.51 [0.36–0.65]), and composite sway ( ρ = 0.48 [0.32–0.62]) were most associated with severity. Base of support widened monotonically with severity and was the most reliable gait feature (intraclass correlation coefficient [ICC] = 0.88). Conclusions Pose‐derived digital endpoints from home‐captured SARA home videos show robust, clinically interpretable correlation with severity, supporting scalable remote phenotyping. Findings motivate longitudinal validation toward clinical and regulatory utility.

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Publication Details

Journal
Movement Disorders Clinical Practice
Published
2026-10-16
DOI
https://doi.org/10.1002/mdc3.70854
Primary Topic
Balance, Gait, and Falls Prevention
Type
article
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article

Remote Video Assessment of Ataxia via SARA home : Correlation of Pose‐Derived Endpoints with Clinician Severity Ratings

Héctor García‐Moreno, Fereshteh Poursaeed, Elin Haf Davies, Elisa Ferrer-Mallol et al.
Movement Disorders Clinical Practice
Balance, Gait, and Falls Prevention
article

Remote Video Assessment of Ataxia via SARA home : Correlation of Pose‐Derived Endpoints with Clinician Severity Ratings

Héctor García‐Moreno, Fereshteh Poursaeed, Elin Haf Davies, Elisa Ferrer-Mallol, Matthis Synofzik, Lisa H. Graf, Thomas Klockgether, Magda M. Santana, Paola Giunti, Marcus Grobe‐Einsler, Jennifer Faber, Dagmar Timmann, Andreas Gustafsson Thieme, Rabia Aziza, Jeannette Hübener‐Schmid, Katharina Hill, Vivian Maas, Arian Taheri Amin
article en

Abstract

Abstract Background Remote assessment of ataxia is increasingly important for patient‐centered care and clinical research. SARA home , a validated video‐based adaptation of the Scale for the Assessment and Rating of Ataxia (SARA), enables self‐administration of key motor tasks at home. Objective The aim was to evaluate the correlation of pose‐derived gait and stance endpoints from SARA home videos with clinician‐rated severity. Methods In a multisite observational study, participants recorded SARA home tasks on consumer mobile devices via the Atom5 TM app. Clinicians rated videos using standardized criteria, blinded to automated outputs. Kinematic measures were extracted via pose estimation and aggregated to video‐level features. Videos were aggregated per participant before correlation using Spearman's ρ and Kendall's τ , with 95% cluster‐bootstrap confidence intervals. Results We analyzed 5418 gait and stance videos from 58 participants across 4 sites (gait n = 2205, stance n = 3213). Score distribution was skewed toward lower severity. For gait, clearance variability ( ρ = 0.52 [0.37–0.64]) and median‐normalized base of support ( ρ = 0.51 [0.35–0.66]) correlated most strongly with item ratings, followed by shoulder sway root mean square ( ρ = 0.43 [0.24–0.60]). Adjusted foot clearance (worse limb) correlated negatively ( ρ = −0.35 [−0.52 to −0.15]). For stance, anteroposterior sway ( ρ = 0.51 [0.36–0.65]), leg alignment variability ( ρ = 0.51 [0.36–0.65]), and composite sway ( ρ = 0.48 [0.32–0.62]) were most associated with severity. Base of support widened monotonically with severity and was the most reliable gait feature (intraclass correlation coefficient [ICC] = 0.88). Conclusions Pose‐derived digital endpoints from home‐captured SARA home videos show robust, clinically interpretable correlation with severity, supporting scalable remote phenotyping. Findings motivate longitudinal validation toward clinical and regulatory utility.

Movement Disorders Clinical Practice
University Hospital Bonn (DE), German Center for Neurodegenerative Diseases (DE), Essen University Hospital (DE), Hertie Institute for Clinical Brain Research (DE), Centro de Neurociências e Biologia Celular (PT), Centro de Inovação em Biomedicina e Biotecnologia (PT), UCL Queen Square Institute of Neurology (GB), Heinrich Heine University Düsseldorf (DE), University College London (GB), University of Duisburg-Essen (DE), University of Coimbra (PT), University of Tübingen (DE)
Openalex Percentile: Top 5%
Balance, Gait, and Falls Prevention
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